Computer Research Articles

U.S. vs. Russia: Cyber «Drang nach Osten»

In June 2022, the commander of U.S. Cyber Command, Paul Nakasone, disclosed that his soldiers had conducted offensive cyberattacks against Russia before the Special military operation in Ukraine began. These so-called “hunt forward” operations are part of USCYBERCOM’s doctrine of persistent engagement. This doctrine involves the personnel of the Cyber Nation Mission Forces deploying to partner countries to work with their cyber defenders in their most critical networks and computer systems. Their mission is to search for and degrade enemy activities, while also researching their tools and tactics in cyberspace. This doctrine is one of Nakasone’s key innovations in Cyber Command’s course of action. Previously, U.S. cyber operations required authorization from the U.S. President. This restriction made actions like persistent engagement and hunt forward operations nearly impossible, as they require extensive activities within other countries’ networks even before a cyberattack is prepared. It is impractical to expect the President to approve every such request. Nakasone changed this by removing the requirement for presidential authorization. Today, this allows Cyber Command to conduct such operations - both defensive and offensive - much more broadly, and they are taking full advantage of this opportunity. The problem lies in the sphere of international law - both in the field of the law of war (jus in bello) and the right to war (jus ad bellum). U.S. politicians often claim that cyber operations can achieve strategic goals without crossing the threshold of armed conflict. In any other domain actions with similar effects could provoke war but not in cyberspace. This feature is its main advantage and the reason the U.S. sabotages other countr ies’ initiatives (particularly Russian) to establish a legal regime for state use of cyberspace. However, there is no consensus among U.S. specialists about the legal basis that legitimizes such operations against another country, both internationally and domestically. Yet, this ambiguity seems to work in the U.S. favor. In fact, U.S. soldiers have attacked another country’s (Russian) territory and this has not led to a direct war between Russia and the U.S. U.S. officials consider the hunt forward operation experience in Ukraine as both successful and useful for refining U.S. strategies in cyberspace, including the National Cybersecurity Strategy and the DoD Cyber Strategy. They plan to use such tools more broadly against Russia. Currently, the U.S. is actively working in the Post-Soviet area against Russia to disrupt Russia’s national interests. Among other things, Washington is attempting to coerce Central Asian states into alignment with U.S. interests. Hunt forward operations are an obvious tool of the United States, which Russia will most likely have to counteract there.

Design and Implementation of a MIPS Datapath

Finally, the integration of these individual components culminates in the execution of the complete MIPS datapath. The MIPS (Microprocessor without Interlocked Pipeline Stages) architecture serves as a widely recognized and utilized instruction set architecture. Implementing the complete datapath involves orchestrating the flow of instructions through the CPU, from instruction fetch to execution and memory access, showcasing the culmination of our efforts in crafting a functional and efficient processor. In essence, this project not only provides a hands-on experience in HDL-based digital design but also immerses us in the intricacies of CPU architecture, emphasizing the importance of each component in achieving a harmonious and high-performance computing system

Atomic Memory Model

Memory leaks and buffer overruns are among the most common erroneous conditions in computer systems. They are also among the most tedious, difficult and time consuming to detect, identify, locate, and resolve. Both Microsoft and Google independently report that memory safety issues cause 70% of all security vulnerabilities [10]. The Atomic Memory Model provides a mechanism for resolving these types of errors. Simultaneously, it makes the software architecture more robust and elegant by enforcing a code hierarchy regarding the memory use, as well as allowing for innate memory abstraction that matches the application semantics. The model also significantly increases the speed of the software development by relieving developers from detailed memory management.

Reservoir computing and advanced synaptic plasticity of sputter-deposited ZnO memristors with controllable threshold and nonvolatile switching behavior

This study presents an ITO/ZnO/ITO/Si memristor fabricated via reactive sputtering for use in advanced analog synaptic plasticity and reservoir computing (RC) systems. The proposed device exhibited stable threshold and nonvolatile switching characteristics by effectively controlling the current compliance (ICC) limit. Multilevel data storage was achieved through controlled multistate switching via reset-stop voltage and ICC. X-ray diffraction analysis confirmed the formation of a polycrystalline ZnO film with a 12:8 oxygen-to-argon ratio, which facilitated the generation of oxygen-vacancy conductive filaments. The memristor effectively replicated key synaptic characteristics such as long-term potentiation, long-term depression, spike-amplitude/width-dependent plasticity, spike-rate-dependent plasticity, and the transition from short-term to long-term memory. The RC system processed binary 4-bit codes and recognized different digits, achieving 98.84% accuracy in handwritten digit recognition using a convolutional neural network simulation, highlighting its potential for efficient image processing applications.

A Wide Range Duty‐Cycle PWM Generator Using Oxide‐TFTs on a Flexible Substrate

ABSTRACTThis work presents an experimental characterization of a novel clocked regenerative comparator with oxide TFT (a‐IGZO) technology on a flexible substrate. The circuit functionality is demonstrated as a wide range duty‐cycle PWM signal generator with a triangular input signal. The regenerative latch in the comparator is implemented with diode‐load–based inverters. The proposed circuit has shown a linear variation in the duty‐cycle from 12% to 84%, when the reference voltage () is varied from 0.5 to 3.3 V, respectively, in the clocked comparator. Further, a reliable operation is observed up to an input signal frequency of 2 kHz at a supply voltage of 4 V, with a power dissipation of 20 W. This circuit would find potential applications in wearable bio‐medical and neuromorphic computational systems.

Empowering DNA-Based Information Processing: Computation and Data Storage.

Information processing is a critical topic in the digital age, as silicon-based circuits face unprecedented challenges such as data explosion, immense energy consumption, and approaching physical limits. Deoxyribonucleic acid (DNA), naturally selected as a carrier for storing and using genetic information, possesses unique advantages for information processing, which has given rise to the emerging fields of DNA computing and DNA data storage. To meet the growing practical demands, a wide variety of materials and interfaces have been introduced into DNA information processing technologies, leading to significant advancements. This review summarizes the advances in materials and interfaces that facilitate DNA computation and DNA data storage. We begin with a brief overview of the fundamental functions and principles of DNA computation and DNA data storage. Subsequently, we delve into DNA computing systems based on various materials and interfaces, including microbeads, nanomaterials, DNA nanostructures, hydrophilic-hydrophobic compartmentalization, hydrogels, metal-organic frameworks, and microfluidics. We also explore DNA data storage systems, encompassing encapsulation materials, microfluidics techniques, DNA nanostructures, and living cells. Finally, we discuss the current bottlenecks and obstacles in the fields and provide insights into potential future developments.

Advanced Signal Processing Techniques for Real-Time Systems in Edge Computing

With the rapid expansion of edge computing, real-time systems are increasingly deployed in environments such as IoT, autonomous vehicles, and industrial applications, where efficient signal processing is crucial for performance and decision-making. However, real-time signal processing in edge computing environments faces significant challenges, including limited computational resources, data transmission constraints, and strict latency requirements. Objective: This paper aims to explore advanced signal processing techniques specifically tailored for real-time systems in edge computing. The goal is to propose novel algorithms and strategies to enhance processing efficiency, reduce latency, and optimize resource usage in these environments. Methods: We propose a combination of traditional signal processing methods and emerging techniques, including: Adaptive Filtering: Improving real-time performance in dynamic environments. Compressed Sensing: Leveraging sparsity to reduce data processing and transmission overhead. Deep Learning Models: Applying convolutional and recurrent neural networks for accurate signal classification and anomaly detection. Distributed Signal Processing: Offloading computation tasks to distributed edge devices to balance load and reduce latency. Results: Experimental results demonstrate that the proposed techniques outperform traditional methods in terms of signal processing speed, resource utilization, and accuracy. In particular, the integration of deep learning models significantly improves classification accuracy for real-time signal detection, while compressed sensing reduces bandwidth requirements without compromising signal quality. Conclusion: The proposed signal processing methods effectively address the unique challenges posed by real-time systems in edge computing environments. These techniques can be applied to a wide range of applications, such as smart cities, industrial IoT, and autonomous systems, providing a solid foundation for the development of efficient, low-latency real-time systems.

Secure Drone Communications using MQTT protocol

With the revolutionary change in emerging technologies, the usage of drones or unmanned aerial vehicles (UAV) has exponentially increased in different sectors like Industry, healthcare, military, agriculture, real estate, manufacturing, logistics, energy and many more utilities. This rapid growth creates a concern for the secure communication between the internal communication modules and the ground based computer system used for controlling the UAV. Intruder can hack into the device and attack the internal communication device with the injection of the malicious code which can lead to the malfunction of the aircraft. Security issues related to the communication between the internal modules of the drone and the ground based computer system is of major concern and is crucial. UAVs have to operate in constrained networks with limited bandwidth. In such a constrained environment MQTT protocol can be an excellent protocol. No cryptographic techniques are used to retain the simplicity and the light weight of the MQTT protocol. This contributes for the large scope for emerging with new solutions in the protection issues of MQTT communications. This paper mainly focuses on Armstrong number encryption standard algorithm for providing a computationally simple yet a secure and strong algorithm for UAVs encryption and decryption process on the communication links using MQTT protocol.

Comparing the Pressure on the Carpal Tunnel When Using an Ergonomic Pointer Driver and an Optical Alternative

Objectives: The objective of this paper is to introduce a method to measure the force or pressure over the carpal tunnel indirectly, using a new device to drive the pointer of a computer system. The measurements were compared with those obtained using an ergonomic mouse. Simultaneously, measurements of muscular stress on the digitorum extensor muscle were performed to correlate the applied force against muscle activity. Methods: An experimental setup was constructed using an infrared static receiver plus two wearable moving light emitters, which can be displaced inside a rectangular projected region. The pointer functions are performed through two finger gestures, while the hand is naturally extended. A microcontroller was used to communicate with the computer, which works as a human interface device and possesses firmware to associate the position of each light source with the pointer functions. Meanwhile, force and electromyography sensing circuits were developed to transmit and measure carpal tunnel strength and muscular stress. The system was tested on five healthy volunteers, who were encouraged to solve the same computational tasks using this new device and a trademark ergonomic mouse. Results: Our results show great differences (greater than one magnitude) between the efforts of the same volunteers performing the same predefined tasks using both pointer controllers. Only when the new device was used did the Pearson’s correlation coefficients show a higher correlation between the effort measured on the carpal tunnel and the muscular activity. Conclusions: The optic pointer driver diminishes the strength on the carpal tunnel, causing slightly increased stress on the digitorum extensor muscle.

Orthopaedic manual therapy in patients with myofascial pain in temporomandibular dysfunction

Background: Temporomandibular dysfunctions are disorders that encompass a set of signs and symptoms such as myofascial pain, decreased mouth opening, cervicalgia, dizziness, tinnitus, and muscle fatigue, among others. Manual therapy, as a conservative treatment of physiotherapy, focuses on pain relief and improvement of its functionality, showing its effectiveness. Objective: To identify whether orthopedic manual therapy improves myofascial pain in patients with temporomandibular dysfunctions. Methods: A quantitative longitudinal methodology was used. The sample consisted of 15 adults aged 20-40 years diagnosed with disc-originated temporomandibular dysfunction disorders at the Type "B" Health Centre of the Government Patronage of Chimborazo Province (Patronato del Gobierno Autónomo Descentralizado Provincial de Chimborazo). The theoretical statistical method used was the T-test or Student's t-test, and the processing of the information to obtain the data was carried out with the SPSS computer system, version 29.0 for Windows in Spanish. Results: Concerning the intervention, the difference is statistically significant in the intensity of pain measured with the Analogue Pain Scale (EVA), the severity of temporomandibular dysfunction measured with the Helkimo index, as well as the people who present anteromedial displacement of the articular disc. The confidence level p=,000 was obtained. Conclusions: orthopedic manual therapy improves the myofascial pain presented by patients with temporomandibular dysfunctions. A significant statistic is evidenced.

AI in Network Infrastructure: Transforming Telecommunications with Intelligent Systems

AI technologies are drastically changing the backbone of telecommunications networks and bringing unheard-of security, network management, and optimization capabilities. From dynamic resource allocation to predictive maintenance and intelligent traffic management, this article shows how artificial intelligence and machine learning technologies are being used to solve important problems in modern telecommunications. By means of a thorough investigation of AI-driven solutions, this article shows that technologies are offering real-time network optimization, automatic threat identification, and improved service dependability while drastically lowering operating costs. While addressing important technical issues and operational considerations, the conversation covers pragmatic solutions across several network domains, including 5G infrastructure, edge computing, and autonomous networking systems. Examining real-world case studies and developing trends helps this article show how artificial intelligence is not only transforming present network operations but also opening the path for future telecommunications innovations, enabling more resilient, efficient, and intelligent network infrastructure that can adapt to changing technological demand and user expectations.

Analysis and selection of the structure of a multiprocessor computing system according to the performance criterion

Objectives. Analysis of the various architectures of computing systems (CSs) used in recent decades has allowed us to identify the most common structures. One of the key features is the use of mass-produced equipment to create data processing subsystems (for example, multicore processors and high-capacity semiconductor memory), as well as network equipment to build communication subsystems. This reduces hardware costs and allows typical or cluster configurations to be created, which is especially important for expensive CSs. The desire to achieve high computational speed and performance in such CSs requires minimizing the time to complete the task and balancing time delays both in data processing subsystems and in the communication subsystem which provides data transmission inside the CS. The aim of this work is to analyze computing modules (CMs) and structures on the basis of which the construction of cluster CSs is carried out.Methods. The main results of the work were obtained using methods of mathematical analysis and modeling.Results. The study considers the structure of modern multicore microprocessors as the basis for building CMs of cluster CSs. As the number of cores in the microprocessor structure increases, the communication network which unites them into a single structure becomes more complicated. It has been shown that in new developments of microprocessors, communication between cores is performed in the form of a network. The microprocessors themselves are MIMD structures in accordance with the well-known Flynn classification.Conclusions. The proposed method of selecting an effective structure of a CS allows us to obtain the optimal structure of a CS according to the criterion of performance.

Company-university intersections through service-learning (SL): a systematic review

The most relevant intersections in society include the relationship between universities and companies for a projection toward the sustainable employability of future graduates. Among the possible intersections, Service-learning (SL) is an educational proposition that may help university students to develop their personal skills, offering them opportunities to learn and practice civic commitment, improving their sense of social and citizen responsibility, and combining academic and community-service learning in a constructed programme where participants train by working on real needs of the environment to optimize and transform the latter. The development of SL programmes in university departments related to technical areas is posing a challenge to faculty members and students, thus it is important to explore this lack of programmes. The main aim of the present study was to identify SL projects and their topics through a systematic review, following the guidelines of the «Preferred Reporting Items for Systematic Reviews and Meta-Analyses» (PRISMA) declaration in the knowledge areas of Architecture, Computer Science, Environmental Engineering, Software Engineering, Computer Engineering, Artificial Intelligence, and Computer Languages and Systems, from the year 2008 to the year 2023. This review includes 128 articles, which were analyzed with ATLAS. Ti 22. The categorical system employed in this work emerged from the topics of the programmes identified in the selected articles, which were verified by experts in the mentioned fields of knowledge. The agreed categories were: accessibility, learning, social groups, courses, devices, infrastructure, games, environment, landscaping, heritage, software and web. The most relevant conclusions highlight that most of the articles refer to theoretical aspects of SL, showing a lack of data on the practical development of SL programmes and their impact on employability. The largest number of SL programmes are developed in the areas of Architecture, Computer Science and Software Engineering. Regarding the topics that are addressed in research, most of the articles refer to social groups, software, learning and accessibility.

Repurposing Drugs for Infectious Diseases by Graph Convolutional Network with Sensitivity-Based Graph Reduction.

Computational systems biology employs computational algorithms and integrates diverse data sources, such as gene expression profiles, molecular interactions, and network modeling, to identify promising drug candidates through repurposing existing compounds in response to urgent healthcare needs. This study tackles the urgent need for rapid therapeutic development against emerging infectious diseases. We introduce a novel analytic expression for sensitivity analysis based on the Kronecker product and enhance model prediction performance using Graph Convolutional Networks (GCNs) with sensitivity-based graph reduction. Our algorithm refines prediction performance by leveraging sensitivity-based graph reduction. By integrating RNA-seq data, molecular interactions, and GCNs, we identify disease-related genes and pathways, construct heterogeneous graph models, and predict potential drugs. This approach involves novel analytical expressions that assess sensitivity to model loss, employing the Kronecker product approach. Subgraph analysis identifies nodes for removal, leading to a refined graph used for model retraining. This cost-effective pipeline focuses on computational methods for drug repurposing, targeting infectious diseases such as Zika virus and COVID-19 infection. Applied to these infections, our methodology integrates 659 proteins and 703 drugs for Zika virus, and 495 proteins and 468 drugs for COVID-19, along with their interactions derived from gene expression profiles. Top candidate drugs, such as Betamethasone phosphate and Bizelesin for Zika virus, and Chloroquine, Heparin Disaccharide, and Resveratrol for COVID-19, were validated through literature review or docking analysis. This scalable approach demonstrates promise in repurposing drugs for urgent healthcare challenges.

Modern methods of personal identification

The article presents a review of current scientific research of using digital computer technology in the practical dental identification, analyzes the main problems of their implementation and actual use. Modern aspects of diagnostics and complex planning of identification research are aimed at increasing the efficiency of solving complex medico-legal issues. The application of digital dental technologies has improved the effectiveness of the process of human identification, as well as the reliability of the provided forensic evidence. Significant advantages of the digital photo and X-ray analysis methods in comparison with traditional ones, as well as the advantages of digital facial 3D-reconstruction and dental identification, indicate the potential benefits of using artificial intelligence technology in order to improve the solution of identification tasks. At the same time, data provided by the specialized literature reveal the imperfections of intelligent methods related to discrimination, transparency, accountability, privacy, data security, ethical standards and other important aspects. In this regard, opinions are expressed about the need to partially limit, up to complete rejection of the use of intelligent computer systems to formulate final conclusions and make final decisions on the results of expert studies. In spite of this, leading specialists of the industry are more and more often cautiously declaring the inevitability of virtual evolution of self-developing artificial intelligence systems designed for autonomous existentialism. Referring to the data of modern scientific research, it is worth noting the growing interest of the scientific community in the issues of implementing digital innovative solutions to ensure the effective solution of everyday scientific and practical tasks. Thus, the potential for the successful application of digital technologies to solve the problems of personal identification and improve the quality of forensic evidence provided remains quite promising.

Exploring Zig-Zag Triangles: H-Coverings and Practical Applications

Graph theory is widely used to analyze the structure models in chemistry, biology, computer science, operations research and sociology. Molecular bonds, species movement between regions, development of computer algorithms, shortest spanning tree in a weighted graphs, aircraft scheduling and exploration of diffusion mechanism are some of these structure models. A computing system C can execute an algorithm A if A is graph-isomorphic to a subgraph of CG. This is equivalent of defining a graph isomorphism between A and subgraph of CG. This research article gives a small description of graph theory applications and one of graph model (zig-zag triangle) to define a suitable computer algorithm. Let Γ be a connected, simple graph with finite vertices v and edges e. A family {Γ1, Γ2, . . . , Γp} ⊂ Γ of subgraphs such that for all e ∈ E, e ∈ Γl, for some l, l = 1, 2, . . . , p is an edge-covering of Γ. If Γl ∼= Γ′, ∀l, then Γ has an Γ′-covering. Graph Γ with Γ′-covering is an (ad, d)-Γ′-antimagic if f : V ∪ E → {1, 2, . . . , |V | + |E|} a bijection exists and the sum over all vertex-weights and edge-weights of Γ′ form a set {ad, ad + d, . . . , ad + (p − 1)d}. The labeling ξ is super for ξ(VΓ) = {1, 2, 3, . . . , |VΓ|} and graph Γ is Γ′-supermagic for d = 0. This manuscript investigates super (ad, d)-Γ′-antimagic labelings of zig-zag triangles for differences d = 1, 2, . . . , 8.

Robotics at the University of Pennsylvania from Birth to Maturity: A Review of 30 Years of Research

This article is an attempt to reexamine the evolution of robotics research at the University of Pennsylvania and all that it entailed, covering the successes and struggles of PhD students, postdoctoral researchers, and a few dedicated faculty between 1972 and 2000. In 1945, Penn's Moore School of Electrical Engineering was famous for developing the first electronic digital computer, ENIAC, but after a few years, the research had diminished. In 1972, a new Department of Computer and Information Science was formed. I came to Penn from Stanford University's Artificial Intelligence Laboratory full of energy, enthusiasm, and the goal of establishing a similar lab at Penn. This article demonstrates the creativity and ingenuity of young professionals at the General Robotics, Automation, Sensing, and Perception (GRASP) Laboratory. We built hardware. We built software. We collaborated with psychologists and electrical and mechanical engineers and tried to build a community of roboticists. Our curiosity led us to build new vision and tactile systems and to investigate cooperative robotics systems on the ground and in the air. We used computational models supported and verified by experiments. Today, I am proud to say that almost all of the students who cycled through the GRASP Lab are successful in academia or industry.

Barycentric and pairwise Rényi quantum leakage with application to privacy-utility trade-off

Barycentric and pairwise quantum Rényi leakages are proposed as two measures of information leakage for privacy and security analysis in quantum computing and communication systems. These quantities both require minimal assumptions on the eavesdropper, i.e. they do not make any assumptions on the eavesdropper’s attack strategy or the statistical prior on the secret or private classical data encoded in the quantum system. They also satisfy important properties of positivity, independence, post-processing inequality and unitary invariance. The barycentric quantum Rényi leakage can be computed by solving a semi-definite program; the pairwise quantum Rényi leakage possesses an explicit formula. The barycentric and pairwise quantum Rényi leakages form upper bounds on the maximal quantum leakage, the sandwiched quantum α -mutual information, the accessible information and the Holevo’s information. Furthermore, differentially private quantum channels are shown to bound these measures of information leakage. Global and local depolarizing channels, that are common models of noise in quantum computing and communication, restrict private or secure information leakage. Finally, a privacy-utility trade-off formula in quantum machine learning using variational circuits is developed. The privacy guarantees can only be strengthened, i.e. information leakage can only be reduced, if the performance degradation grows larger and vice versa .

Multi-Agent Cooperation for Computing Power Scheduling in UAVs Empowered Aerial Computing Systems

Multi-Agent Cooperation for Computing Power Scheduling in UAVs Empowered Aerial Computing Systems

Artificial intelligence technologies and ethics in educational processes: solution suggestions and results

Artificial intelligence is a technology used to imitate the human-like thinking and decision-making abilities of computer systems. This technology enables computers to perform complex tasks such as data analysis, learning, problem solving and decision making. It is used in the field of education as well as in every field. While the use of artificial intelligence in the field of education provides advantages such as providing personalized learning experiences to students, providing teachers with intuition about student performance and developing educational materials, the ethical dimension should not be ignored. Therefore, the aim of this study is to produce solutions to ethical problems in the teaching and evaluation processes of artificial intelligence technologies in education. Qualitative research method was used in this study. It has adopted the phenomenological research approach among qualitative research methods. The concept of phenomenon is also the ethics of artificial intelligence. The working group consists of teachers, educational technologists and academicians. When selecting the working group, it was taken into consideration that there were teachers who use artificial intelligence applications in education and academics and technologists working in this field. Document analysis and focus group interviews were used as data collection tools. Content analysis was performed on the data obtained. According to the results of the study, ethical problems encountered with the use of artificial intelligence in education were identified and solution suggestions were offered.